How Big Data Integrations Disrupt Markets

Startups are becoming more and more consumer-friendly. The use of Big Data to personalize experiences is making the jobs of startups easier and the lives of buyers better. Big Data integration combined with the gritty innovation inherent to startups is resulting in disruptors in many industries.

Perhaps the most obvious example is Uber. The way that the taxi industry operated had not changed much in over 50 years. Before Uber, it wasn’t uncommon to get into a cab that only accepted cash (we’re talking 2010, here). The industry had grown accustomed to a captive audience — one that really had no other option than to follow the status quo and flag down cabs on city sidewalks.

By tapping the resource that most riders have at the ready — a smartphone — Uber was able to completely disrupt its own industry by offering more options to consumers. Uber uses consumer data to help steer experiences, too, from tracking the ride and offering to share it with friends to saving and suggesting destinations. Instead of standing in the rain hoping for a cab with its light on, consumers started tapping on their phones inside the comfort of their offices or hotels. The convenience of requesting a ride and paying for the ride quickly showed consumers what they had been missing for decades. The rest, as they say, is history.

After the initial disruption by Uber, other players have come on the ride-sharing scene like Lyft and Sidecar, providing more competition and ultimately more options for consumers. The taxi industry will never be the same, though, thanks to Uber’s smart use of consumer data as a disruptor. Putting more power into the hands of consumers in exchange for Big Data and tracking has proved the perfect combination for a once-small startup that harnessed technology to turn an entire industry on its head.

While the Uber example is one that most people recognize, lesser-known startups are causing disruptions in their industries through Big Data integrations. What exactly are they doing that is working so well?

Mobile App Insistence

If you really want to understand consumer behavior, you have to go with them on their journeys — all of them. Startups that find ways to incorporate with mobile applications are able to track what consumers are doing — and not only when they are using the app at hand. This allows the startup to then know exactly when to offer a discount or location reminder. When consumers also opt-in to text messaging, startups can reach them on an even more personal level and with perfect timing.

Tracking Big Data through mobile devices is one vital way that Big Data is leveling the playing field for startups. The technology offers ways for startups to deliver custom offers and concierge services that traditional, established businesses may overlook. A startup that truly wants to optimize Big Data details must have a user-friendly mobile app and as a bonus must offer text message opting-in.

Targeted Customizations

Instead of giving consumers the option to offer information about their spending habits and interests (which they often aren’t completely aware of in the first place), startups can use Big Data to piece together individual consumers. This allows for tailored offerings that reach buyers at the right moment, resulting in higher sales. Targeted customization through Big Data analysis isn’t relegated to physical products, either. Financial products like small business loans, fitness suggestions for gyms or virtual trainers, and more can all be offered to consumers at opportune times when past behavior and reasonable assertions through Big Data are tapped.

Social and Other Online Mentions

Understanding what consumers are saying about a brand goes a long way to improving it. Startups today have the advantage of tracking what is being said on a variety of platforms, including social ones. While most startups cannot afford a full-time team to monitor brand mentions online, hiring a specialization team to do so is a reasonable option. Startups are good at knowing who is saying what about them and when and then responding. Online mentions aren’t always overt, either. The startups that find a way to extrapolate behavior based on what people are doing and not necessarily saying succeed.